15.5K skills · sorted by popularity
Design and review REST APIs with consistent resource names, HTTP status codes, error responses, and pagination, which splits lists into smaller results. It also guides filtering, authentication, request limits, and versioning for public or internal APIs.
Organize engineering work carried out by AI agents with clear completion criteria, small verifiable tasks, and evaluations before and after implementation. Match model choice to task complexity and track tokens, retries, time, and outcomes to manage cost.
Build or review server-side APIs in Node.js, Express, and Next.js. Apply patterns for organizing business logic and data access, reducing unnecessary database queries, caching results, validating requests, and handling authentication and errors.
Coordinate coding projects through Claude DevFleet by splitting work into dependent tasks and dispatching Claude Code agents in separate Git working directories. Monitor progress, manage automatic task sequencing, and review structured reports of changes, tests, and errors.
Integrate x402, an HTTP payment protocol, so agents can pay for APIs or services. Configure task and session budgets, approved recipients, and wallets with privately managed keys, using integration paths for Base, X Layer, or Solana.
Define team processes for codebases largely implemented by AI agents. Covers planning, ownership rules, architecture, review criteria, and testing requirements, helping teams assess generated code through measurable acceptance criteria, system behavior, and regression checks.
Review how easy code is to maintain using CodeScene MCP. Compare structural health scores before and after edits, identify design issues, and check commits and pull requests for changes that reduce maintainability.
Build shared interfaces for Android, iOS, Desktop, and Web with Compose. This skill guides screen state, navigation, reusable components, themes, and rendering performance, including ways to handle interface differences between platforms.
Create CodeTour files that guide readers through a codebase step by step, with verified file and line references. Tailor the walkthrough to new contributors, architecture readers, PR reviewers, or investigators tracing a failure or security boundary.
Diagnose failed AI agent runs by capturing errors, checking likely causes, and choosing small, reversible recovery actions. The workflow produces a structured report of the failure, recovery steps, and evidence, helping explain repeated retries or stalled progress.
Build a project-specific ECC installation plan using evidence from code and configuration. Sort skills, rules, hooks, and other components into items loaded every session and references kept available for occasional use.
Create Angular components and services with guidance on state management, forms, and navigation. Adapt implementation choices to the project's Angular version, and check the resulting code through tests and builds.
Access paid APIs using Machine Payments Protocol (MPP), a protocol for request payments. The skill checks payment requirements, selects a compatible wallet or client, submits payment, and helps inspect the API response and receipt.
Turn a codebase into an interactive graph of code relationships. Explore functions, call chains, related groups, and execution flows in a browser, with optional Cloudflare tunneling to share the explorer remotely.
Add an AI assistant to an existing web app so users can operate its interface with everyday instructions. Covers embedding the panel, connecting a language model, testing interactions, and protecting API keys in production.
Search and rewrite code by its syntax structure, such as function definitions or calls. Preview changes across files before applying them, and use YAML rules for repeatable checks and automatic fixes.
Carry out an implementation plan by assigning each task to a fresh subagent, a separate agent with its own context. Review specification compliance first, then code quality, repeat fixes as needed, and finish with an integration review.
Turn code changes and system structure into animated SVG diagrams. The skill maps changed components, surrounding context, and ordered data flows, then helps prepare diagrams for sharing in pull requests or through an optional published link.
Test a plan before implementation through structured, challenging questions. Work through decisions in dependency order, receive recommendations with each question, and finish with a clear account of agreed choices, open issues, and scope.
Diagnose REST and GraphQL API failures by checking connectivity, authentication, request formats, and returned data. Prepare reproducible commands, identify likely causes, and build regression tests that check whether a fix keeps working.
Record a website's network traffic in a HAR file, a log of requests and responses, then derive an HTTP client from its JSON requests. Reuse captured request details to run searches or fetch data without repeated browser interaction.
Build Python MCP servers that let AI agents use APIs, databases, and file workflows. MCP is a connection standard for agent tools. The skill covers starter templates, local testing, client registration, and deployment as HTTP endpoints.
Helps you discover, authenticate, and call MCP servers from the terminal. MCP connects agents to external tools. You can inspect available tools, manage connections, make one-off calls, and generate command-line wrappers or TypeScript clients.
Generate an interactive bash script that guides people through manual service setup. It opens relevant pages, explains what to click, collects credentials, and saves values to .env files or GitHub secrets with stage confirmations.